https://github.com/thatsinewave/monte-carlo-engine

A web-based simulation tool that leverages the Monte Carlo method to generate probabilistic outcomes based on user-defined parameters.
https://github.com/thatsinewave/monte-carlo-engine

good-first-contribution good-first-issue good-first-issues good-first-pr good-first-pr-first-contribution good-first-prs iterations monte-carlo monte-carlo-integration monte-carlo-methods monte-carlo-sampling monte-carlo-simulation montecarlo montecarlo-simulation probability probability-distribution simulation simulator thatsinewave visualization

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A web-based simulation tool that leverages the Monte Carlo method to generate probabilistic outcomes based on user-defined parameters.

• Host: GitHub
• URL: https://github.com/thatsinewave/monte-carlo-engine
• Owner: ThatSINEWAVE
• License: mit
• Created: 2025-03-10T21:42:51.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2025-03-11T03:39:42.000Z (about 2 months ago)
• Last Synced: 2025-03-11T04:26:47.758Z (about 2 months ago)
• Topics: good-first-contribution, good-first-issue, good-first-issues, good-first-pr, good-first-pr-first-contribution, good-first-prs, iterations, monte-carlo, monte-carlo-integration, monte-carlo-methods, monte-carlo-sampling, monte-carlo-simulation, montecarlo, montecarlo-simulation, probability, probability-distribution, simulation, simulator, thatsinewave, visualization
• Language: JavaScript
• Homepage: https://thatsinewave.github.io/Monte-Carlo-Engine/
• Size: 452 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md

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README

        


# [Monte Carlo Engine](https://thatsinewave.github.io/Monte-Carlo-Engine)

![Banner](https://raw.githubusercontent.com/ThatSINEWAVE/Monte-Carlo-Engine/refs/heads/main/.github/SCREENSHOTS/Monte-Carlo-Engine.png)

Monte Carlo Engine is a web-based simulation tool that leverages the Monte Carlo method to generate probabilistic outcomes based on user-defined parameters. It allows users to input variables, set ranges and weights, and run randomized simulations to analyze probability distributions and interactions.

 

**Live Demo:** [Monte Carlo Engine](https://thatsinewave.github.io/Monte-Carlo-Engine)



## Features

- **Dynamic Parameter Input** – Define multiple parameters with adjustable min/max values and weights.

- **Monte Carlo Simulation** – Runs thousands of randomized trials to generate outcome distributions.

- **Probability Analysis** – Displays top outcomes with probability percentages.

- **Interaction Effects** – Simulates parameter dependencies and influences.

- **Visualizations** – Interactive bar charts and pie charts for insights.

- **Customizable Iterations** – Choose simulation intensity for accuracy vs. speed.



## ☕ [Support my work on Ko-Fi](https://ko-fi.com/thatsinewave)



## Installation & Usage

The Monte Carlo Engine is a browser-based tool, and no installation is required. Simply visit the [live demo](https://thatsinewave.github.io/Monte-Carlo-Engine) or clone the repository for local use.

### Run Locally

1. Clone the repository:

   ```bash

   git clone https://github.com/thatsinewave/Monte-Carlo-Engine.git

   cd Monte-Carlo-Engine

   ```

2. Open `index.html` in a web browser.

## How It Works

1. Add parameters (name, range, weight).

2. Set the number of iterations (higher = more accuracy).

3. Run the simulation.

4. View probability distributions and parameter influences.



## [Join my discord server](https://discord.gg/2nHHHBWNDw)



## Contributing

Feel free to submit issues or contribute improvements via pull requests.

## License

This project is open-source and available under the [MIT License](LICENSE)